Jonathan Binas

PhD Student
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I was trained as a physicist at ETH Zurich before joining INI for a PhD. I have always been interested in the interdisciplinary field of neural computation, where biology, physics, mathematics, engineering, and computer science meet.

I am most interested in learning and self-organization in spiking neural networks. During my PhD, I work on models of probabilistic computation in recurrent neural assemblies and use neuromorphic VLSI devices to emulate large, spiking neural networks.



  • Binas J., Indiveri G., and Pfeiffer M. Local Structure Helps Learning Optimized Automata in Recurrent Neural Networks, IEEE International Joint Conference on Neural Networks (IJCNN), 2015 pdf
  • Diehl, P.U. and Neil, D. and Binas, J. and Cook, M. and Liu, S.C. and Pfeiffer, M. Fast-Classifying, High-Accuracy Spiking Deep Networks Through Weight and Threshold Balancing, IEEE International Joint Conference on Neural Networks (IJCNN), 2015 pdf




  • Neftci, Emre and Binas, Jonathan and Chicca, Elisabetta and Indiveri, Giacomo and Douglas, Rodney Systematic Construction of Finite State Automata Using VLSI Spiking Neurons, Biomimetic and Biohybrid Systems 382-383, 2012
© 2015 Institut für Neuroinformatik